计算机科学与探索2024，Vol.18Issue(3)：627-645,19.DOI:10.3778/j.issn.1673-9418.2310062
卷积神经网络在结直肠息肉辅助诊断中的应用综述
Review of Application of Convolutional Neural Network in Auxiliary Diagnosis of Colorectal Polyps
摘要
Abstract
Colorectal cancer is a malignant tumor that mainly occurs in the tissues of the colon and rectum,and its early detection and treatment are of great significance.The early detection and prevention of colorectal cancer mainly involves visual examination of the patient's intestines to screen for colorectal polyps,but manual examination has the disadvantage of high misdiagnosis rate.The auxiliary diagnostic system based on convolutional neural networks(CNN)has shown the most advanced performance in the diagnosis of colorectal polyps,and is currently a research hotspot in the field of computer-aided diagnosis.Based on important literature published in recent years,a systematic review of the application of convolutional neural networks in the auxiliary diagnosis of colorectal polyps is conducted.Firstly,the commonly used datasets in the field of colorectal polyp diagnosis are introduced,including image and video datasets.Secondly,the application of CNN in colorectal polyp detection,segmentation,and classification is systematically elaborated.The main improvement ideas,advantages and disadvantages,and performance of each al-gorithm are analyzed in depth,aiming to provide researchers with a more systematic reference,and summarize the interpretability of deep learning models.Finally,a summary of various algorithms for assisting the diagnosis of colorectal polyps based on CNN is provided,and future research directions are prospected.关键词
结直肠息肉/卷积神经网络(CNN)/计算机辅助诊断/可解释性Key words
colorectal polyps/convolutional neural networks(CNN)/computer aided diagnosis/interpretability分类
信息技术与安全科学引用本文复制引用
考文涛,李明,马金刚..卷积神经网络在结直肠息肉辅助诊断中的应用综述[J].计算机科学与探索,2024,18(3):627-645,19.基金项目
国家自然科学基金面上项目(82074579,82174528) （82074579,82174528）
2022年山东省研究生优质教育教学资源项目(SDYAL2022041).This work was supported by the National Natural Science Foundation of China(82074579,82174528),and the Graduate High-Quality Education Teaching Resources Project of Shandong Province in 2022(SDYAL2022041). （SDYAL2022041）
